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    <meta name="description" content="纸上得来终觉浅，绝知此事要躬行  距离我“入门”机器已经半年了，之所以是假入门，是因为平时课程实在是太繁重了，刷均分，赶作业，完全顾不上认真学习。因为渐渐的觉得每周跟的组会上面研究生学长分享的那些东西听不太懂，是为基础过于薄弱，同时又进入了一个数据挖掘的课题组，不能当个半吊子(知识点懂一半，代码不会写)啥都不懂，所以打算趁着寒假时间还算充足，把《机器学习实战》上的算法都实现一遍（主要代码与内容">
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<meta property="og:title" content="机器学习实战第一课——KNN近邻算法">
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<meta property="og:description" content="纸上得来终觉浅，绝知此事要躬行  距离我“入门”机器已经半年了，之所以是假入门，是因为平时课程实在是太繁重了，刷均分，赶作业，完全顾不上认真学习。因为渐渐的觉得每周跟的组会上面研究生学长分享的那些东西听不太懂，是为基础过于薄弱，同时又进入了一个数据挖掘的课题组，不能当个半吊子(知识点懂一半，代码不会写)啥都不懂，所以打算趁着寒假时间还算充足，把《机器学习实战》上的算法都实现一遍（主要代码与内容">
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9LYqLi9GhQ4dQEIiIx+PBP/7xD7z88sto3749cnJyNOWJJAiC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%0AJMMoAIqIiIhkGAVAERERkQzzHxJqzlyrG88rAAAAAElFTkSuQmCC">
<meta property="article:published_time" content="2020-01-16T02:52:52.000Z">
<meta property="article:modified_time" content="2020-03-01T13:21:52.882Z">
<meta property="article:author" content="宇航猫休蛰">
<meta property="article:tag" content="机器学习">
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9LYqLi9GhQ4dQEIiIx+PBP/7xD7z88sto3749cnJyNOWJJAiC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%0APtzc7ku9UyU4DvjrX4GEBOP7CLRebMYMYMECOhLPd3uVlUCrVlW1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<h2 id="纸上得来终觉浅绝知此事要躬行"><a class="markdownIt-Anchor" href="#纸上得来终觉浅绝知此事要躬行"></a> <strong>纸上得来终觉浅，绝知此事要躬行</strong></h2>
</blockquote>
<p>距离我“入门”机器已经半年了，之所以是假入门，是因为平时课程实在是太繁重了，刷均分，赶作业，完全顾不上认真学习。因为渐渐的觉得每周跟的组会上面研究生学长分享的那些东西听不太懂，是为基础过于薄弱，同时又进入了一个数据挖掘的课题组，不能当个半吊子(知识点懂一半，代码不会写)啥都不懂，所以打算趁着寒假时间还算充足，把《机器学习实战》上的算法都实现一遍（主要代码与内容学习还是参考apachecn的github所得）。<br />
　　今天复现的是K-近邻算法，是所有机器学习算法中最简单的之一[wiki]，主要思想是求出测试数据与全体训练数据集之间的欧氏距离，然后对欧氏距离进行排序，返回前k个距离最短的样本数据集，这k个数据项中出现次数最多的标签即为测试数据的预测标签。为防止各种标签在k个最短距离数据项中只出现一次，k应该大于标签类别数（我瞎猜的，应该是这样）<br />
　　我的python基本上处于一个入门阶段，今天实操一遍，收获颇丰，也深感能力之不足，同志仍需努力。<br />
　　KNN没有训练过程，只有一次一次的计算与比较，所以说它的空间复杂度与计算复杂度都很高，下面是用python复现的代码<br />
总的代码如下</p>
<h3 id="1-准备模块"><a class="markdownIt-Anchor" href="#1-准备模块"></a> 1. 准备模块</h3>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">from</span> __future__ <span class="keyword">import</span> print_function</span><br><span class="line"><span class="keyword">from</span> numpy <span class="keyword">import</span> *</span><br><span class="line"><span class="keyword">import</span> operator</span><br><span class="line"><span class="keyword">from</span> os <span class="keyword">import</span> listdir</span><br><span class="line"><span class="keyword">from</span> collections <span class="keyword">import</span> Counter</span><br><span class="line"><span class="keyword">import</span> matplotlib</span><br><span class="line"><span class="keyword">import</span> matplotlib.pyplot <span class="keyword">as</span> plt</span><br></pre></td></tr></table></figure>
<ul>
<li>__future__模块可以引用未来版本python库中的函数，其实我的版本已经是3.x，所以没有必要走这一步</li>
<li>将numpy导入有多种方法，一般常用import numpy as np，这里的这种方法可以不加前缀直接调用numpy中的函数如zeros，这种方式类似于C语言中的名称空间</li>
</ul>
<h3 id="2数据读取模块"><a class="markdownIt-Anchor" href="#2数据读取模块"></a> 2.数据读取模块</h3>
<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br></pre></td><td class="code"><pre><span class="line">fr&#x3D;open(&quot;E:\MachineLearning\KNN\dataset\datingTestSet2.txt&quot;)</span><br><span class="line">numberOfLines&#x3D;len(fr.readlines())</span><br><span class="line">fr.seek(0)</span><br><span class="line">returnMat&#x3D;zeros((numberOfLines,3))</span><br><span class="line">classLabelVector&#x3D;[]</span><br><span class="line">index&#x3D;0</span><br><span class="line">for line in fr.readlines():</span><br><span class="line">    line&#x3D;line.strip()</span><br><span class="line">    listFromLine&#x3D;line.split(&#39;\t&#39;)</span><br><span class="line">    returnMat[index,:]&#x3D;listFromLine[0:3]</span><br><span class="line">    classLabelVector.append(int(listFromLine[-1]))  # classLabelVector 与 returnMat 一一对应，前者为所属标签，后者为具体数据</span><br><span class="line">    index+&#x3D;1</span><br></pre></td></tr></table></figure>
<ul>
<li>这一部分呢，强调一下文件的读取，如今数据挖掘与数据分析方面更常用pandas，不过目前还不需要那么高深的功能，以后再用。</li>
<li>readlines()会按行读取数据（读取所有行并返回list），读取完毕之后指向最后一个字符，所以如果需要重新读取，要用seek(0)指向初始位置<br />
接下来strip()函数可以删去str的头或尾的换行符或者空格或者，指定字符（需指明参数）</li>
<li>split()函数指定分隔符对str进行切片，在本代码中将str分成四个list，前三个为数据，存入returnMat中，最后一个是标签，用append()方法存入classLabelVector中</li>
<li>returnMat的数据结构为array，矩阵结构在存入数据时可以利用index索引，了解的不是很全，目前只知道这一个用法，以后再分析</li>
</ul>
<h3 id="3可视化模块"><a class="markdownIt-Anchor" href="#3可视化模块"></a> 3.可视化模块</h3>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br></pre></td><td class="code"><pre><span class="line">labels=classLabelVector</span><br><span class="line">plt.figure(figsize=(<span class="number">8</span>, <span class="number">5</span>), dpi=<span class="number">80</span>)</span><br><span class="line">axes = plt.subplot(<span class="number">111</span>)</span><br><span class="line"> <span class="comment">#将三类数据分别取出来</span></span><br><span class="line"> <span class="comment">#x轴代表飞行的里程数</span></span><br><span class="line"> <span class="comment">#y轴代表玩视频游戏的百分比</span></span><br><span class="line">type1_x = []</span><br><span class="line">type1_y = []</span><br><span class="line">type2_x = []</span><br><span class="line">type2_y = []</span><br><span class="line">type3_x = []</span><br><span class="line">type3_y = []</span><br><span class="line"><span class="keyword">for</span> i <span class="keyword">in</span> range(len(labels)):</span><br><span class="line">    <span class="keyword">if</span> labels[i] == <span class="number">1</span>:  <span class="comment"># 不喜欢</span></span><br><span class="line">        type1_x.append(returnMat[i][<span class="number">0</span>])</span><br><span class="line">        type1_y.append(returnMat[i][<span class="number">1</span>])</span><br><span class="line">    <span class="keyword">if</span> labels[i] == <span class="number">2</span>:  <span class="comment"># 魅力一般</span></span><br><span class="line">        type2_x.append(returnMat[i][<span class="number">0</span>])</span><br><span class="line">        type2_y.append(returnMat[i][<span class="number">2</span>])</span><br><span class="line">    <span class="keyword">if</span> labels[i] == <span class="number">3</span>:  <span class="comment"># 极具魅力</span></span><br><span class="line">        type3_x.append(returnMat[i][<span class="number">0</span>])</span><br><span class="line">        type3_y.append(returnMat[i][<span class="number">3</span>])</span><br><span class="line">type1 = axes.scatter(type1_x, type1_y, s=<span class="number">20</span>, c=<span class="string">'red'</span>)</span><br><span class="line">type2 = axes.scatter(type2_x, type2_y, s=<span class="number">40</span>, c=<span class="string">'green'</span>)</span><br><span class="line">type3 = axes.scatter(type3_x, type3_y, s=<span class="number">50</span>, c=<span class="string">'blue'</span>)</span><br><span class="line">plt.xlabel(<span class="string">'Miles earned per year'</span>)</span><br><span class="line">plt.ylabel(<span class="string">'Percentage of events spent playing video games'</span>)</span><br><span class="line">axes.legend((type1, type2, type3), (<span class="string">u'dislike'</span>, <span class="string">u'Charismatic'</span>, <span class="string">u'Very attractive'</span>), loc=<span class="number">2</span>,)</span><br><span class="line">plt.show()</span><br></pre></td></tr></table></figure>
<p>为了让画出来的图好看，指定不同标签不同颜色，所以画点的时候分三次，得到的图如下所示<img src="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%0AJMMoAIqIiIhkGAVAERERkQzzHxJqzlyrG88rAAAAAElFTkSuQmCC" alt="可视化" /></p>
<h3 id="4归一化"><a class="markdownIt-Anchor" href="#4归一化"></a> 4.归一化</h3>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br></pre></td><td class="code"><pre><span class="line">normMat=zeros((numberOfLines,<span class="number">3</span>))</span><br><span class="line"><span class="keyword">for</span> i <span class="keyword">in</span> [<span class="number">0</span>,<span class="number">1</span>,<span class="number">2</span>]:</span><br><span class="line">    max=returnMat[:,i].max()</span><br><span class="line">    min=returnMat[:,i].min()</span><br><span class="line">    <span class="keyword">for</span> j <span class="keyword">in</span> range(<span class="number">1000</span>):</span><br><span class="line">        normMat[j,i]=(returnMat[j,i]-min)/(max-min)</span><br><span class="line"><span class="comment"># done</span></span><br></pre></td></tr></table></figure>
<p>归一化是将所有数据都映射到一个固定的区间之中，上述方法是在[0,1]区间之间，这么做的目的是使各类数据的权重保持一致，保证某一类数据的影响不会强于其他<br />
<strong>常见归一化方法有:</strong></p>
<ul>
<li>线性转换： newValue=(oldValue-min)/(max-min) max和min为该组数据集中的最大最小特征值</li>
<li>对数转换： y=log10(x)</li>
<li>反余切转换：y=arctan(x)*2/PI</li>
</ul>
<h3 id="5knn算法部分"><a class="markdownIt-Anchor" href="#5knn算法部分"></a> 5.KNN算法部分</h3>
<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br></pre></td><td class="code"><pre><span class="line">inx=[<span class="number">0.40166314</span>, <span class="number">0.56719748</span>, <span class="number">0.52034602</span>] <span class="comment"># 作为输入的样本</span></span><br><span class="line">dataSetSize=normMat.shape[<span class="number">0</span>]</span><br><span class="line">diffMat = tile(inx, (dataSetSize,<span class="number">1</span>))-normMat</span><br><span class="line">sqDiffMat = diffMat**<span class="number">2</span></span><br><span class="line">distances=(sqDiffMat.sum(axis=<span class="number">1</span>))**<span class="number">0.5</span></span><br><span class="line">sortedDistIndicies = distances.argsort() <span class="comment"># argsort()函数是将x中的元素从小到大排列，提取其对应的index(索引号)，所以并不会影响对应的label的值</span></span><br><span class="line"><span class="comment"># k取5</span></span><br><span class="line">classCount=&#123;&#125;</span><br><span class="line"><span class="keyword">for</span> i <span class="keyword">in</span> range(<span class="number">5</span>):</span><br><span class="line">    voteIlabel = labels[sortedDistIndicies[i]]</span><br><span class="line">    classCount[voteIlabel] = classCount.get(voteIlabel,<span class="number">0</span>) + <span class="number">1</span></span><br><span class="line">sortedClassCount = sorted(classCount.items(), key=operator.itemgetter(<span class="number">1</span>), reverse=<span class="literal">True</span>)</span><br></pre></td></tr></table></figure>
<p>其实到了这一部分发现难度反而没有前面的高，可能是因为这个算法比较简单<br />
<strong>值得注意的点有:</strong></p>
<ul>
<li>tile()函数用来对数组进行复制第二个参数(x,y)分别表示行复制多少次，列复制多少次</li>
<li>argsort()函数是将x中的元素从小到大排列，提取其对应的index(索引号)，所以并不会影响对应的label的值</li>
<li>classCount是一个构造字典的过程，对字典还不太熟，但今天的一天的已经结束了，没精力再去深究了，不干了，睡大觉<br />
<strong>第一天的工作，over！</strong></li>
</ul>
<hr />
<p>DAY 2 对KNN算法进行一个总结（来自apachecn上的小结，在此做一个备份）：<br />
<strong>近似误差与估计误差</strong></p>
<ul>
<li>近似误差：可以理解为对现有训练集的训练误差。</li>
<li>估计误差：可以理解为对测试集的测试误差。</li>
</ul>
<p>近似误差关注训练集，如果近似误差小了会出现过拟合的现象，对现有的训练集能有很好的预测，但是对未知的测试样本将会出现较大偏差的预测。模型本身不是最接近最佳模型。</p>
<p>估计误差关注测试集，估计误差小了说明对未知数据的预测能力好。模型本身最接近最佳模型。</p>
<p>推荐使用交叉验证<a href="https://zhuanlan.zhihu.com/p/24825503" target="_blank" rel="noopener">[知乎]</a><a href="https://zh.wikipedia.org/wiki/%E4%BA%A4%E5%8F%89%E9%A9%97%E8%AD%89" target="_blank" rel="noopener">[wiki]</a><a href="https://blog.csdn.net/lhx878619717/article/details/49079785" target="_blank" rel="noopener">[CSDN]</a>选取合适的k值（交叉验证是一种评估统计分析、机器学习算法对独立于训练数据的数据集的泛化能力）</p>
<p><strong>距离度量 Metric/Distance Measure</strong></p>
<p>度量距离除了本文中用的欧氏距离之外，还可以是Minkowski距离或者曼哈顿距离（更多细节可以参看 sklearn 中 valid_metric 部分）</p>
<p><strong>算法</strong><br />
算法：（sklearn 上有三种）</p>
<ul>
<li>Brute Force 暴力计算/线性扫描（数据结构中学过的BF算法，暴力模式匹配）</li>
<li>KD Tree 使用二叉树根据数据维度来平分参数空间<a href="https://www.cnblogs.com/eyeszjwang/articles/2429382.html" target="_blank" rel="noopener">[博客园]</a>。对高维数据处理时经常会用到</li>
<li>Ball Tree 使用一系列的超球体来平分训练数据集。（Ball Tree了解的不是很多）</li>
</ul>
<p><font color=red><strong>最后，在这里附上apachecn/AiLearning的<a href="https://github.com/apachecn/AiLearning" target="_blank" rel="noopener">github</a>，里面有非常丰富的AI领域学习资料，收获颇丰，十分感谢</strong></font></p>

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            <p>原文作者：<a href="http://xiuzhedorothy.gitee.io">宇航猫休蛰</a>
            <p>原文链接：<a href="http://xiuzhedorothy.gitee.io/2020/01/16/ji-qi-xue-xi-shi-zhan-di-yi-ke-knn-jin-lin-suan-fa/">http://xiuzhedorothy.gitee.io/2020/01/16/ji-qi-xue-xi-shi-zhan-di-yi-ke-knn-jin-lin-suan-fa/</a>
            <p>发表日期：<a href="http://xiuzhedorothy.gitee.io/2020/01/16/ji-qi-xue-xi-shi-zhan-di-yi-ke-knn-jin-lin-suan-fa/">January 16th 2020, 10:52:52 am</a>
            <p>更新日期：<a href="http://xiuzhedorothy.gitee.io/2020/01/16/ji-qi-xue-xi-shi-zhan-di-yi-ke-knn-jin-lin-suan-fa/">March 1st 2020, 9:21:52 pm</a>
            <p>版权声明：本文采用<a rel="license noopener" href="http://creativecommons.org/licenses/by-nc/4.0/" target="_blank">知识共享署名-非商业性使用 4.0 国际许可协议</a>进行许可</p>
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        <ol class="toc"><li class="toc-item toc-level-2"><a class="toc-link" href="#纸上得来终觉浅绝知此事要躬行"><span class="toc-number">1.</span> <span class="toc-text"> 纸上得来终觉浅，绝知此事要躬行</span></a><ol class="toc-child"><li class="toc-item toc-level-3"><a class="toc-link" href="#1-准备模块"><span class="toc-number">1.1.</span> <span class="toc-text"> 1. 准备模块</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#2数据读取模块"><span class="toc-number">1.2.</span> <span class="toc-text"> 2.数据读取模块</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#3可视化模块"><span class="toc-number">1.3.</span> <span class="toc-text"> 3.可视化模块</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#4归一化"><span class="toc-number">1.4.</span> <span class="toc-text"> 4.归一化</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#5knn算法部分"><span class="toc-number">1.5.</span> <span class="toc-text"> 5.KNN算法部分</span></a></li></ol></li></ol>
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